شبیه‌سازی عمقی شوری خاک با استفاده از زنجیره مارکف در باغات پسته اردکان

Akramkhanov, A., Martius, C., Park, S.J. and Hendrickx, J.M.H. (2011). Environmental factors of spatial distribution of soil salinity on flat irrigated terrain. Geoderma, 163, 55–62.

Bierkens, M.F.P. and Weerts, H.J.T. (1994). Applications of indicator simulation to modeling the lithological properties of a complex confining layer. Geoderma, 62, 265–284.

Bogaert, P. (2002). Spatial prediction of categorical variables: The Bayesian maximum entropy approach. Stochastic Environmental Research and Risk Assessment, 16, 425–448.

Carle, S.F. and Fogg, G.E. (1997). Modeling spatial variability with one- and multi-dimensional continuous Markov chains. Mathematical Geosciences, 29, 891–918.

Christakos, G. (1990). A Bayesian/maximum-entropy view to the spatial estimation problem. Mathematical Geosciences, 22, 763–777.

D’Or, D. and Bogaert, P. (2004). Spatial prediction of categorical variables with the Bayesian maximum entropy approach: the Ooypolder case study. European Journal of Soil Science, 55, 763–775.

Deutsch, C.V. (1998). Cleaning categorical variable (lithofacies) realizations with maximum a-posteriori selection. Computers and Geosciences, 24, 551–562.

Elfeki, A.M. and Dekking, F.M. (2001). A Markov chain model for subsurface characterization: Theory and applications. Mathematical Geosciences, 33, 569–589.

Goovaerts, P. (1997). Stochastic simulation of categorical variables using a classification algorithm and simulated annealing. Mathematical Geosciences, 28, 909–921.

Johnson, N.L. (1949). Systems of frequency curves generated by methods of translation. Biometrika, 36, 149–176.

Journel, A.G. (1983). Nonparametric estimation of spatial distributions. Mathematical Geosciences, 15, 445–468.

Journel, A.G. and Isaaks, E.H. (1984). Conditional indicator simulation: application to a Saskatchewan uranium deposit. Journal of the International Association of Mathematical Geology, 16, 685–718.

Kyriakidis, P.C. and Dungan, J.L. (2001). Stochastic simulation for assessing thematic classification accuracy and the impact of inaccurate spatial data on ecological model predictions. Environmental and Ecological Statistics, 17, 1083-1098.

Li, W. (2006). Transiogram: A spatial relationship measure for categorical data. International Journal of Geographical Information Science, 20, 693–699.

Li, W. and Zhan, C. (2005). Application of transiograms to Markov chain simulation and spatial uncertainty assessment of land-cover classes. GIScience and Remote Sensing, 42, 297–319.

Li, W., Li, B. and Shi, Y. (1999). Markov-chain simulation of soil textural profiles. Geoderma, 92, 37–53.

Li, W., Zhang, C., Burt, J.E., Zhu, A.X. and Feyen, J. (2004). Two-dimensional Markov chain simulation of soil type spatial distribution. Soil Science Society of America Journal, 68, 1479–1490.

Malone, B.P., McBratney, A.B., Minasny, B. and Laslett, G.M. (2009). Mapping continuous depth functions of soil carbon storage and available water capacity. Geoderma, 154, 138–152.

Marsily, G., Delay, F., Goncalves, J., Renard, P., Teles, V. and Violette, S. (2005). Dealing with spatial heterogeneity. Hydrogeology Journal, 13, 161–183.

Miller, J. and Franklin, J. (2002). Modeling the distribution of four vegetation alliances using generalized linear models and classification trees with spatial dependence. Ecological Modelling, 157, 227–247.

Minasny, B. and McBratney, A.B. (2006). A conditioned Latin hypercube method for sampling in the presence of ancillary information. Computers and Geosciences, 32, 1378–1388.

Rahimian, H., Noori, M., Hasheminejad, Y., Tabatabayi, H. and Neshat, E. (2014). Determination of leaching fraction for pistachio orchards in Ardakan using wetting front detector and electromagnetic induction techniques. Journal of Soil Research, 28, 163-173. (in Farsi)

Sheather, S.J. (1992). The performance of six popular bandwidth selection methods on some real data sets (with discussion). Computational Statistics, 7, 225–281.

Silverman, B.W. (1981). Using kernel density estimates to investigate multimodality. Journal of the Royal Statistical Society, 43, 97–99.

Taghizadeh-Mehrjardi, R., Minasny, B., Sarmadian, F. and Malone, P.B. (2014). Digital mapping of soil salinity in Ardakan region, central Iran. Geoderma, 213, 15-28.

Thompson, D.K. and Waddington, J.M. (2014). A Markov chain method for simulating bulk density profiles in boreal peatlands. Geoderma, 232, 123-129.

Weissmann, G.S. and Fogg, G.E. (1999). Multi-scale alluvial fan heterogeneity modeled with transition probability geostatistics in a sequence stratigraphic framework. Journal of Hydrology, 226, 48–65.

Wu, K., Nunan, N., Crawford, J.W., Young, I.M. and Ritz, K. (2004). An efficient Markov chain model for the simulation of heterogeneous soil structure. Soil Science Society of America Journal, 68, 346–351.

Zhang, C. and Li, W. (2008). A comparative study of nonlinear Markov chain models for conditional simulation of multinomial classes from regular samples. Stochastic Environmental Research and Risk Assessment, 22, 217–230.